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A Bayesian multivariate receptor model for estimating source contributions to particulate matter pollution using national databases

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  • Amber J. Hackstadt
  • Roger D. Peng

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  • Amber J. Hackstadt & Roger D. Peng, 2014. "A Bayesian multivariate receptor model for estimating source contributions to particulate matter pollution using national databases," Environmetrics, John Wiley & Sons, Ltd., vol. 25(7), pages 513-527, November.
    • Handle: RePEc:wly:envmet:v:25:y:2014:i:7:p:513-527
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    Cited by:

    1. Oliver Baerenbold & Melanie Meis & Israel Martínez‐Hernández & Carolina Euán & Wesley S. Burr & Anja Tremper & Gary Fuller & Monica Pirani & Marta Blangiardo, 2023. "A dependent Bayesian Dirichlet process model for source apportionment of particle number size distribution," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
    2. Matthew Heiner & Taylor Grimm & Hayden Smith & Steven D. Leavitt & William F. Christensen & Gregory T. Carling & Larry L. St. Clair, 2023. "Multivariate receptor modeling with widely dispersed Lichens as bioindicators of air quality," Environmetrics, John Wiley & Sons, Ltd., vol. 34(3), May.

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